Session list
We have a wide range of topics available, from the latest trends to technical sessions!
For more advanced level sessions, you can narrow down your search by "Technical Sessions."
Filter sessions by category
Keynote speech: AI TRISM/AI Security/Generative AI
Legal issues regarding the use of data and generative AI
This seminar will cover basic topics such as the legal nature of data and the legal nature of data license agreements, as well as clauses that should be included in data-related contracts, points to be aware of, and common mistakes to make. In addition, based on the experience of having already filed dozens of patent applications related to generative AI and formulating many terms of use for services using generative AI and internal rules regarding the use of generative AI, this seminar will provide an easy-to-understand explanation of points to be aware of and legal issues when using generative AI or services using generative AI as a company.
iCraft Law Office Lawyer and Patent Attorney
Mr. Makoto Uchida
Mr. Makoto Uchida
He specializes in building intellectual property strategies related to AI and IT, and building legal strategies for personal information and data businesses. He is a member of the working group for the Ministry of Economy, Trade and Industry's "AI and Data Contract Guidelines Review Committee." He has been selected twice in the intellectual property category of the lawyer rankings conducted by the weekly Toyo Keizai magazine.
Keynote speech, technical session, generative AI
Evolving AI technology and a "human-centered approach" in companies
The progress of AI in recent years has been remarkable. In particular, the emergence of generative AI and its rapid evolution have amazed the world on a daily basis. In this presentation, I will discuss the trends in AI technology, touching on key technologies ("world models" and "probabilistic programming").
We will also explain the future direction of AI utilization in companies, referring to the concept of "Human-Centered AI," which is gaining attention.
We will also explain the future direction of AI utilization in companies, referring to the concept of "Human-Centered AI," which is gaining attention.
Hakuhodo DY Holdings Inc.
Executive Officer
CAIO (Chief AI Officer) / Representative of Human Centered AI Institute
Mr. Masaya Mori
Executive Officer
CAIO (Chief AI Officer) / Representative of Human Centered AI Institute
Mr. Masaya Mori
After working for a consulting firm and an internet company, he joined a professional firm and is engaged in supporting companies in the digital transformation field. He is a professor at Tohoku University, an advisor for the Collaborative Platform Development at the University of Tokyo, and an advisor for the Japan Deep Learning Association.
keynote speech
Generative AI 2.0
～From Prompt Engineering to Beyond～
It has been about a year and a half since the introduction of generative AI. While companies have achieved some success in idea generation, translation, and summarization, they are aware of the challenges of taking the next step. What kind of changes are necessary to make more advanced use of generative AI?
In this session, entitled "Generative AI 2.0 - From Prompt Engineering to Beyond," we will invite people who have been pioneers in generative AI to discuss the use of in-house data through RAG (Search Augmented Generation) and the incorporation of generative AI into business processes. Let's think together about a concrete path toward the use of next-generation AI.
In this session, entitled "Generative AI 2.0 - From Prompt Engineering to Beyond," we will invite people who have been pioneers in generative AI to discuss the use of in-house data through RAG (Search Augmented Generation) and the incorporation of generative AI into business processes. Let's think together about a concrete path toward the use of next-generation AI.
Rohto Pharmaceutical Co., Ltd.
Executive Officer CIO and Head of IT/AI Promotion Office
Mr. Yuichi Itabashi
Executive Officer CIO and Head of IT/AI Promotion Office
Mr. Yuichi Itabashi
Joined Fujifilm as a chemical engineer in 1985. In R&D, he developed a groundbreaking digital color printing technology using microcapsules. To commercialize the technology, he moved from R&D to the Imaging Division, and in the midst of the crisis of losing his main business due to the digitization of photography, he worked on business transformation through commercialization and marketing of digital cameras and digital printing systems, and also led the revival of the Instax business. He then contributed to the company's management transformation using digital technology as head of the Digital Marketing Office and ICT Strategy Office. In 2021, he joined Rohto Pharmaceutical and promoted the company's digital transformation and use of AI as Executive Officer CIO and Head of the IT/AI Promotion Office.
Digil Co., Ltd.
Representative Director and President
Keiji Taguchi
Representative Director and President
Keiji Taguchi
He has led strategic IT/DX initiatives at a major telecommunications company, a foreign information security company, a major retail company, and a real estate group company. He is currently engaged in support consulting for companies that continue to take on challenges, focusing on corporate transformation, DX promotion, and in-house organization construction.
Impress Corporation.
Editor-in-chief, IT Leaders Producer
Jun Taguchi
Editor-in-chief, IT Leaders Producer
Jun Taguchi
Macnica
Data & Application Division Deputy General Manager
Kosuke Onishi
Data & Application Division Deputy General Manager
Kosuke Onishi
Generative AI, data management, data infrastructure, case study presentations
The challenge of reducing labor hours by 1.4 million hours per year using generative AI
Nihon Kohden Corporation (hereinafter, Nihon Kohden) has decided to aim to "reduce 1.4 million man-hours per year" by utilizing generative AI as part of a company-wide profit reform. In this presentation, we will introduce the trajectory of the Business Strategy Department, which aims to create an environment where anyone can reduce man-hours by using generative AI, including how to handle a wide variety of internal data and how to make users adopt generative AI in order to effectively introduce and utilize it at the company.
Nihon Kohden Corporation
Business Strategy Division Business Strategy Division
Leader of Generative AI Development Promotion Division
Mr. Yuta Okumura
Business Strategy Division Business Strategy Division
Leader of Generative AI Development Promotion Division
Mr. Yuta Okumura
In 2010, he joined Nihon Kohden Corporation, a medical equipment manufacturer. He developed the Holter ECG monitor as an electrical engineer for 11 years. After that, he was involved in process improvement based on TOC for the entire company. From 2023, he will lead the company-wide use of generative AI.
Nihon Kohden Corporation
Ogino Memorial Institute, AI Technology Development Division / Expert, Generative AI Development Promotion Division, Business Strategy Department, Business Strategy Division
Mr. Wataru Matsuzawa
Ogino Memorial Institute, AI Technology Development Division / Expert, Generative AI Development Promotion Division, Business Strategy Department, Business Strategy Division
Mr. Wataru Matsuzawa
Joined Nihon Kohden Corporation in 1997. Engaged in biosignal processing and medical AI development at the research institute. Since 2023, engaged in the development of generative AI systems to improve the efficiency of in-house operations.
The goal is to reduce labor hours by 1.4 million hours per year by fiscal 2026.
The goal is to reduce labor hours by 1.4 million hours per year by fiscal 2026.
Macnica
Data & Application Division
Data & AI Platform Business Department, Section 1
Arisa Yamamoto
Data & Application Division
Data & AI Platform Business Department, Section 1
Arisa Yamamoto
Generative AI, latest trends, technical sessions
"The path to realizing generative AI applications using in-house data" from the perspective of the latest overseas technologies
The realization of generative AI applications using in-house data is attractive to many companies, but the road to achieving this is not always smooth. While the importance of fine tuning and RLHF (Reinforcement Learning from Human Feedback) has been pointed out, in recent years, there are limitations to the accuracy of RAG (Retrieval-Augmented Generation) alone, and the use of it in combination with Knowledge Graph has attracted attention.
In this seminar, we will look back at how to create generative AI applications using in-house data, based on cutting-edge information from overseas, and introduce common challenges and the technologies that have emerged as solutions.
We hope you will take advantage of this opportunity to learn about the latest technological trends for introducing AI into enterprise environments.
In this seminar, we will look back at how to create generative AI applications using in-house data, based on cutting-edge information from overseas, and introduce common challenges and the technologies that have emerged as solutions.
We hope you will take advantage of this opportunity to learn about the latest technological trends for introducing AI into enterprise environments.
Macnica Networks USA
Vice President
Seio Ohara
Vice President
Seio Ohara
Data management/data infrastructure
Accelerate your business by improving customer experience!
A DX support specialist discusses the issue of "fragmented customer data" and how to solve it
In today's world, life revolves around web services, and user expectations are rising. For this reason, many companies are focusing on utilizing customer data and improving services, aiming to "improve customer experience" as the key to growing their business. In this session, we welcome Mr. Ohashi from Flect, who will explain examples of companies that have worked to improve customer experience, and the best practices he felt through these examples. What is the "fragmented customer data" that companies are actually facing? This session is full of hints for improving business value. Please take this opportunity to participate.
Flect Co., Ltd.
Board Director and COO, Cloud Integration Division
Business Division Manager
Mr. Masaoki Ohashi
Board Director and COO, Cloud Integration Division
Business Division Manager
Mr. Masaoki Ohashi
Macnica
Data & Application Division
Daichi Seshita
Data & Application Division
Daichi Seshita
Macnica
Security Division 3
Masashi Ikeda
Security Division 3
Masashi Ikeda
Case studies, latest trends, data management/data infrastructure
Only one year left until the 2025 cliff!
- Advancing Japan's Digital Transformation with the help of IT powerhouse India -
The term "2025 Cliff" was first used in the "DX Report" published by the Ministry of Economy, Trade and Industry in 2018. Are you ready?
In this session, together with Celebal Technologies, a technology company from India, which has now become an IT powerhouse, we will discuss the current state of Japan's DX when viewed from a global perspective, data technology, and global examples.
In this session, together with Celebal Technologies, a technology company from India, which has now become an IT powerhouse, we will discuss the current state of Japan's DX when viewed from a global perspective, data technology, and global examples.
Celebal Technology Co., Ltd.
Senior Sales Manager
Mr. Yoshiro Inoue
Senior Sales Manager
Mr. Yoshiro Inoue
Celebal Technology Co., Ltd.
Associate Consultant Sales
Shino Kawagoe
Associate Consultant Sales
Shino Kawagoe
Macnica
Data & Application Division
Data & AI Platform Business Department Manager
Satoshi Ohtaki
Data & Application Division
Data & AI Platform Business Department Manager
Satoshi Ohtaki
Data management/data infrastructure
Three points necessary for constructing and enhancing SCM with an eye on 2030 to survive the VUCA era
In this era of rapid global change and uncertainty about the future, establishing and enhancing supply chain management (SCM), particularly in the manufacturing industry, can be said to be an important measure.
In this session, Macnica, a company that provides technology-based consulting, and BrainPad, a pioneer in data utilization, will discuss key points for building and enhancing SCM with an eye to the future from three management perspectives.
① Agile data management that captures uncertainty
②Global risk management
3) Knowledge management for sustainable management
This book will be especially useful for those who will be building and enhancing SCM in the future, so we hope you enjoy it.
In this session, Macnica, a company that provides technology-based consulting, and BrainPad, a pioneer in data utilization, will discuss key points for building and enhancing SCM with an eye to the future from three management perspectives.
① Agile data management that captures uncertainty
②Global risk management
3) Knowledge management for sustainable management
This book will be especially useful for those who will be building and enhancing SCM in the future, so we hope you enjoy it.
BrainPad Inc.
Analytics Consulting Unit
Senior Manager
Mr. Shota Okazaki
Analytics Consulting Unit
Senior Manager
Mr. Shota Okazaki
BrainPad Inc.
Sales & Marketing Unit
Enterprise Sales Lead
Ryo Hayakawa
Sales & Marketing Unit
Enterprise Sales Lead
Ryo Hayakawa
BrainPad Inc.
Sales & Marketing Unit
Alliance Lead
Mr. Yusuke Awai
Sales & Marketing Unit
Alliance Lead
Mr. Yusuke Awai
Macnica
DX Consulting Division
General Manager
Norikazu Miyagi
DX Consulting Division
General Manager
Norikazu Miyagi
Macnica
DX Consulting Division
Assistant Director of New Business Emergence Consulting Office
Ryosuke Yoshida
DX Consulting Division
Assistant Director of New Business Emergence Consulting Office
Ryosuke Yoshida
AI TRISM/AI Security, Generative AI, Technical Session
A successful strategy for using generative AI
~Risk management techniques~
Are you familiar with the term AI TRiSM, which has been gaining attention recently?
AI TRiSM is an abbreviation of Trust, Risk, and Security Management, and is an initiative to address AI risks and increase the reliability of AI.
As the adoption of AI progresses, various risks are becoming apparent, such as malicious attacks on AI models and unintended information leaks, making how to ensure the security and reliability of AI a major issue.
In this seminar, we will specifically introduce the risks contained in AI models and training data, and provide a detailed explanation of the latest measures and methods for protecting data privacy and improving the reliability of AI models.
Please join us for this opportunity to learn cutting-edge technologies for safely utilizing generative AI and enhance your business competitiveness.
AI TRiSM is an abbreviation of Trust, Risk, and Security Management, and is an initiative to address AI risks and increase the reliability of AI.
As the adoption of AI progresses, various risks are becoming apparent, such as malicious attacks on AI models and unintended information leaks, making how to ensure the security and reliability of AI a major issue.
In this seminar, we will specifically introduce the risks contained in AI models and training data, and provide a detailed explanation of the latest measures and methods for protecting data privacy and improving the reliability of AI models.
Please join us for this opportunity to learn cutting-edge technologies for safely utilizing generative AI and enhance your business competitiveness.
Macnica
Data & Application Division, Data & AI Platform Business Department, Section 2
Daichi Kakinuma
Data & Application Division, Data & AI Platform Business Department, Section 2
Daichi Kakinuma
Generative AI, Case studies, Technical sessions, Data management/Data infrastructure
Tips for introducing generative AI into your company, learning from common "failure patterns"
~The path to transforming technical support through LLM~
"We want to utilize generative AI technology to improve the efficiency of our operations."
These needs are increasing against the backdrop of the rapid development of generative AI in recent years. However, there are several hurdles to overcome in terms of system and business application in order to introduce and implement generative AI into actual business operations. In this presentation, we will provide hints on using generative AI, including common failure patterns and solutions, based on a case study of LLM use in a department in charge of customer inquiries about products handled.
These needs are increasing against the backdrop of the rapid development of generative AI in recent years. However, there are several hurdles to overcome in terms of system and business application in order to introduce and implement generative AI into actual business operations. In this presentation, we will provide hints on using generative AI, including common failure patterns and solutions, based on a case study of LLM use in a department in charge of customer inquiries about products handled.
Macnica
Networks Company Data & Application Division 1st Technology Department 1st Section
Kyoichi Sugimoto
Networks Company Data & Application Division 1st Technology Department 1st Section
Kyoichi Sugimoto
Generative AI, technical sessions, data management/data infrastructure
Data structuring in the age of generative AI
- Image and text extraction practice using multimodal LLM -
One of the applications of generative AI, which has made rapid progress in recent years, is the extraction of structured data from unstructured data such as images and text. In this session, we will introduce a concrete example of the implementation of information extraction from fashion product images using multimodal LLM, and explain how to solve the problems of efficiency and personal dependency in creating structured data manually.
Macnica
AI Solution Planning Office Chief
Kazutaka Ikeda
AI Solution Planning Office Chief
Kazutaka Ikeda
Generative AI Technical Session
Generative AI for utilizing confidential data that is difficult to use on the cloud
- Thinking about local LLM using NVIDIA as an example -
It has been about two years since the appearance of ChatGPT, which shocked the world. Generative AI is at the center of the technology trend, and various companies are considering using generative AI.
On the other hand, due to data protection considerations, cloud services do not allow the use of valuable data such as personal and confidential information, and in some cases, the use of generative AI does not progress as expected.
In this session, we will discuss the current status of use of generative AI, as well as the challenges it faces, and discuss the key points to consider when building a local LLM in an on-premises environment using NVIDIA's SDK.
On the other hand, due to data protection considerations, cloud services do not allow the use of valuable data such as personal and confidential information, and in some cases, the use of generative AI does not progress as expected.
In this session, we will discuss the current status of use of generative AI, as well as the challenges it faces, and discuss the key points to consider when building a local LLM in an on-premises environment using NVIDIA's SDK.
Macnica
Clavis Company, 1st Technology Division, 4th Technology Department, 1st Section
Kawabe Kuga
Clavis Company, 1st Technology Division, 4th Technology Department, 1st Section
Kawabe Kuga
Generative AI/Case Study
At the forefront of business process transformation using generative AI
The key to adoption is creating a system for co-creation with users!
Generative AI is a powerful tool for streamlining and transforming business processes, but there are many hurdles to overcome when it comes to implementing it. In this session, we will explain the specific methods for using generative AI in business operations while clarifying the reasons and issues that have hindered its implementation, such as the reluctance of users to use generative AI and the challenges of using internal data. We will also explain the key points for maximizing the potential of generative AI, suggesting effective ways to use it, and promoting its use in business operations.
Macnica
General Manager, Incubation Office, New Business Headquarters
Masayuki Hayashi
General Manager, Incubation Office, New Business Headquarters
Masayuki Hayashi
Data management/data infrastructure
The key is at the "edge"! "Collection" and "analysis" are essential for future data utilization
In today's world, where data exists in various places and in large quantities, many customers are likely to face the following challenges.
"We are not able to collect the data necessary to utilize it for business purposes." "There is a lot of noise in the data, so we are not able to analyze it effectively."
"Edge" is the key to solving these issues. Edge refers to a location close to the data source. In the future, it will be important to "collect" more types of data from the edge and "analyze" the data on the edge side.
In this session, we will explain how the "edge" can be used to solve modern data utilization issues, including specific use cases and solutions.
"We are not able to collect the data necessary to utilize it for business purposes." "There is a lot of noise in the data, so we are not able to analyze it effectively."
"Edge" is the key to solving these issues. Edge refers to a location close to the data source. In the future, it will be important to "collect" more types of data from the edge and "analyze" the data on the edge side.
In this session, we will explain how the "edge" can be used to solve modern data utilization issues, including specific use cases and solutions.
Macnica
Data & Application Division, 1st Technology Department, 2nd Section
Deputy manager
Tomoki Kawamura
Data & Application Division, 1st Technology Department, 2nd Section
Deputy manager
Tomoki Kawamura
